Urban infrastructure serves as a crucial vehicle for understanding urban development and spatial transformation and is a central focus of urban political ecology research. However, the complex socio-natural dialectics and sociopolitical processes underlying these infrastructures have received limited attention within the Chinese academic context. This article focuses on urban hydraulic infrastructure, employing a qualitative systematic review and bibliometric analysis to examine 157 English-language articles indexed in the Web of Science database from 1987 to 2024. The findings reveal that international research on urban political ecology has evolved along multiple pathways, primarily encompassing political-economic analysis from a neo-Marxist perspective, micro-political analysis from a post-structuralist perspective, and everyday practice analysis from a post-humanist perspective. Within these analytical frameworks, scholars have explored pressing issues such as the commodification, modernization, and re-naturalization of hydraulic infrastructure, uncovering the complex power dynamics and "informal" governance practices embedded within these processes. These studies also critically examine how capitalism shapes and reinforces unequal access to water-related ecological services and disparities in urban living experiences. The ontological and analytical frameworks developed in international urban political ecology literature offer significant value for understanding the implementation and spatial production processes of hydraulic infrastructure amid the Chinese urbanization. Furthermore, the rich experiences in China—particularly in terms of state-capital relations, state-society interactions, and socio-natural dynamics—hold great potential for advancing and enriching existing theories of urban political ecology.

Political ecology, with its critical focus on uncovering the embedded social, economic, and political power structures underpinning environmental issues, has emerged as a key interdisciplinary field garnering growing attention from the international academic community. This article offers a comprehensive examination of the development of the global political ecology academic community by analyzing published literature, transnational research networks, university institutions, NGOs, and the digital presence of individual scholars. It identifies and interprets the structural characteristics, developmental trajectories, and future prospects of this academic network.The study finds that political ecology has been heavily influenced by feminism and post-structuralism, resulting in a critically oriented research paradigm. The political ecology community is marked by a high degree of interdisciplinarity, a decentralized and networked organizational form, and a commitment to digitalization and open access scholarship. Furthermore, knowledge production within the field is characterized by a globalization of environmental concerns and a localization of empirical case studies. The rising prominence of Global South perspectives and a strong orientation toward praxis and transformative social engagement are also salient features of current research.However, the article also highlights several ongoing challenges, including increasing theoretical fragmentation and persistent inequalities in knowledge production between the Global North and South. At the same time, the evolving geopolitical landscape, rapid advancements in digital technology, and the escalating urgency of global environmental crises—particularly climate change—present significant opportunities for reinvigorating and expanding the scope and impact of political ecology.

The construction and development of protected areas not only has the important significance of maintaining the stability of the ecosystem, but also contains spatial political practices involving resource allocation, spatial construction, and multi-party power play. Based on the perspective of political ecology, this study was guided by national policies, and took different actors, namely the local government and villagers of Qi'ao Island, as the research objects, and used qualitative research methods to analyze the development process of Qi'ao Island Mangrove Nature Reserve. The study found that the spatial construction and power relationship evolution of the Qi'ao Island Mangrove Nature Reserve have gone through four stages, namely, resource development and ecological marginalization led by villagers' livelihoods, government-led ecological control and game, co-governance and power structure adjustment under mitigation policies, and scientific spatial planning and power resilience construction under the background of blue carbon ecology. Through the interpretation of these four stages, the transformation of power relations in the mangrove nature reserve of Qi'ao Island is clarified, in order to provide relevant suggestions for the development of other nature reserves and provide relevant reference solutions for the harmonious coexistence of local people and nature.

Spatial econometrics has been widely used in the Chinese literature for more than 20 years. Spatial econometric models can be found in many disciplinary fields, which on the one hand denotes the rapid popularity of spatial econometric models and on the other hand indicates the wide range of applications of spatial econometric models. However, because spatial econometrics covers a wide range of knowledge in geography, econometrics, and geographic information systems, it is a typical interdisciplinary discipline. Hence, quite a lot of problems have arisen in its application. This paper systematically summarizes the most common problems of spatial econometric models in empirical studies, as well as more in-depth explanations in these problems, in an effort to help economics and social sciences researchers correctly apply these spatial econometric models. This paper first introduces the concept of spatial effects, which are the core of spatial data analysis and spatial econometric models; then discusses some problems of spatial weight matrices in empirical analysis, including the advantages and disadvantages of various types of spatial weights matrices, as well as the importance of matrix standardization; then summarizes the most common problems in drawing thematic choropleth maps, especially the advantages and disadvantages of various classification methods. The article then focuses on spatial autocorrelation analysis, including the important notes in application of the Moran's I test and the differences and linkages between Moran's I statistic and spatial autoregressive coefficient. Finally, it summarizes and analyzes the main problems of spatial econometric models in empirical analysis, including the scope of application of different spatial econometric models, whether to consider multiple spatial interaction effects in the models, and how to select the appropriate spatial weights matrix to construct spatial econometric models. In addition, it also introduces the scale and hypothesis testing of the GWR model in empirical applications.

Spatial econometric models can be used to capture spatial dependence within data. These models have found extensive application in disciplines such as economics, management and network analyses. Bayesian methods, such as Markov Chain Monte Carlo algorithms, have addressed many limitations of classical approaches, hence significantly advancing both theoretical and applied research. With the growing availability of large datasets and advancements in computational methods, Bayesian estimation methods are required not only to provide accurate estimates but also to balance computational efficiency. This study examines three state-of-the-art Bayesian methods, i.e., Hamiltonian Monte Carlo (HMC), Integrated Nested Laplace Approximations (INLA), and Variational Inference (VI). Various Monte Carlo simulation experiments were conducted to evaluate the performance of them under different sample sizes and key parameters. The results demonstrate that all three methods exhibit good performance. HMC excels for small sample sizes, whereas INLA demonstrates superior computational efficiency for large datasets. The VI method serves as an effective complement to the first two methods. This study provides theoretical guidance for researchers applying Bayesian techniques to spatial econometric models and practical insights for empirical analysts selecting suitable estimation methods based on computational constraints.

Understanding and grasping the spatial pattern of China's population aging and the factors influencing it is of great significance for optimizing the allocation of elderly care resources, and targeting the formulation of population development strategies. Under the perspective of spatial heterogeneity, the spatial and temporal patterns of population aging and influencing factors of Chinese cities at prefecture level and above are studied based on three national census data in 2000, 2010 and 2020, using multiple linear regression models and multi-scale geographically weighted regression models. The results show that: 1. China's population overall aging accelerated and deepened during the study period, most notably in Jiangsu and Sichuan provinces, with strong positive spatial correlation characteristics of the aging pattern among cities, and the overall pattern remained stable; 2. Chinese cities in general shifted from adult to senior across types, with senior cities transitioning from early to mid-late stage; 3. The hot and cold spots of aging showed spatial evolution characteristics, with the hot spots showing a "two-cluster" pattern and the cold spots gradually shrinking; 4. Ageing was affected by demographic, economic, public service, education and environmental factors, with birth rate, death rate and migration rate acting as the dominant factors, and other factors changing in stages; 5. The influence of demographic factors on population aging has shifted from global to local and from robust to non-robust, the spatial heterogeneity of the influence of economic, medical and educational factors on aging has undergone periodic changes; and the significance of environmental factors has gradually emerged.

The optimization of industrial spatial structure is pivotal for urban economic growth. This study introduces an innovative framework to evaluate the optimization of industrial spatial structures and assesses the levels of such optimization across 284 Chinese cities from 2003 to 2021, utilizing three geographical matrices—latitude and longitude distance, commuting time, and commuting distance—to develop a spatiotemporal weight matrix based on the Kronecker product concept. Building on this foundation, the research employs panel spatial econometric models, complemented by robustness checks, endogeneity treatments, and heterogeneity analyses, to dissect the economic growth effects stemming from the optimization of industrial spatial structures. The results underscore the significant role that optimizing industrial spatial structures plays in fostering economic growth, an impact that surpasses that of traditional input factors like capital and labor. Nonetheless, the pace of improvement in the optimization of industrial spatial structures across China has been gradual during the period under review, with noticeable regional disparities in the economic growth effects of such optimization. In light of these findings, the study advocates for elevating the level of industrial spatial structure optimization, harnessing the synergistic interactions between macro and micro dimensions of industrial spatial structures, and stimulating inter-regional collaborative development in optimizing industrial spatial structures to propel sustained economic growth.

Based on an unbalanced panel composed of 3 222 observation samples of 267 cities and a balanced panel composed of 3 808 observation samples of 238 cities constructed by the random forest method from 2003 to 2018, we construct both the unbalanced and balanced panel spatial Durbin error models to study the spatial evolution and influencing factors of urban construction land in China. The study reveals the following spatiotemporal evolution characteristics: 1. Since 2003, China's per capita urban construction land has generally exhibited a continuous upward trend. Even based on the underestimated values defined in this study, it has approached the upper limit (115 m²/person) stipulated in the 2012 updated Urban Land Classification and Planning Construction Land Standard. 2.With the exception of megacities, where per capita urban construction land has shown an overall decline, the other six city categories demonstrated significant growth trends.Regarding influencing factors: 1. Urban scale expansion significantly reduces per capita urban construction land. 2. Current economic development and urbanization rates still promote the increase of per capita urban construction land, indicating that these drivers have not yet transitioned to a phase of promoting intensive land use. 3. Per capita urban construction land is also influenced by neighboring cities'urban scales, economic development levels, industrial structures, and openness.

Rapid urbanization and climate change are rapidly changing earth and the earth systems. This paper explores the new tasks and new frontiers of Chinese geography from the perspective of the Anthropocene. As a crucial discipline within earth sciences, geography spans the natural and social sciences and is poised to become the most promising field in the era of Anthropocene. It is a new mission of geography to define the spatiotemporal structure of anthroposphere, rebuild the framework of the human-environment relationships, conduct research on topology of the human geography, return to research on sustainable development based on the unified geography. Human geography, as the most important branch of geography, will be reshaped for rapid world urbanization, climate change and sustainable issues. For historical geography, it needs to pay greater attention to the impact of human activities, such as the history of prehistoric marine civilization and continental civilization, as well as the history of the modern environmental pollution. For economic geography, it could be on finance-trade-globalization, global value chains-global production chains-global industrial chains, of course the "global South"will be becoming a hot spot and of focus. Due to the collectivization of western countries centered on the United States, the trend of deglobalization and the increasing risk of the new cold war, political geography is in urgent development need. It could be shifting from geopolitics to global governance, rebuilt an effective global institution for cooperation that belong fields of unconventional and new energy technologies. For social geography, it would prioritize social issues on the global perspective, especially as rapid world urbanization and global climate change have inequalities of race, gender, class and some other social groups. Information technology and the Internet have given Cultural Geography new connotations and new opportunities for development. It is necessary to pay special attention to the significance of human beings' use of various words and semiotics tools to the planet and its place where human being live, and explore more effective countermeasures to intervene in rapid earth change. In response to the accelerated processes of urbanization, climate and earth changes, Urban Geography should swiftly transition from a traditional framework focused on "urbanization-urban systems-internal urban structures" to a new framework focusing on modernization based on green growth. It is very likely that Anthropocene geography will give geographers some new disciplines to develop imaginary fields, such as deep sea and deep space exploration, planetary geography, interstellar colonization and migration.

Basic hypothesis is the logical starting point for any disciplines; however, the regional school believes that basic hypothesis is not needed because geography is more concerned with the exploration of regional individuality and the analysis of regional differences. Obviously, this view, while addressing the application of geography and meeting the need for problem-oriented researches, but differs from the general definition of science. The basic hypothesis of the spatial school is homogeneous space (plain), according to which a corresponding theoretical system is constructed, which is more in line with the general scientific definition. Although scholars have previously pointed out the defect that the views the spatial school holds were too abstract, then they fell into a socialized and microscopic path of development, which apparently does not solve the problem of the path of development of the spatial school or even the discipline of human geography. This paper argues that the spatial school, starting from the basic hypothesis of homogeneous space, does not answer the locational question (from a geographic perspective) of the generation of (the first) city, although it solves the question of the mechanism of the generation of (the first) city (from an economic perspective) through the spatial polarization effect. For this reason, the basic hypothesis of human geography needs to be redefined, i.e., homogeneous spaces need to be replaced with homogeneous regions. The latter differs from the former in that there is a clear boundary range, thus homogeneous regions have locational value function attribute, regional scale attribute, regional open state attribute, etc. Thus, reconstructing the basic hypothesis not only addresses the existing inherent deficiencies of the spatial school (it is so abstract as to be divorced from geography), also supplements the basic hypothesis for the existing regional school (which is less restricted to basic assumptions and more focused on application). On this basis, this paper integrates the combined effects of spatial polarization effect, distance attenuation effect, regional edge effect and allometric growth effect, to construct a regional spatial structure theory system, which is composed of point elements, linear elements and area elements. Besides, point structure theory, axis structure theory and area structure theory are also integrated in the regional spatial structure theory this paper conducts.

Data is one of the most crucial issues in achieving sustainable development in rural areas. Hitherto, emerging techniques, like remote sensing and machine learning, provide a promising foundation aiming at the data acquisition, calculation, and analysis, especially for vast, scattered, and full of territory heterogeneity villages. Specifically, the methodology of the Computable Village establishes the imagery-figure relationship via deriving systematically the multi-sourced data of rural natural and human settlement subjects; besides describing various rural elements quantificationally levering index calculating, data mining, and Artificial Intelligence methods, which could further unveil the spatial discrepancy and dynamic tendency of rural development in the total territory, and thus provides a possibility for rural researches striding from local to global. In this paper, a technical framework of the Computable Village is proposed including: (1) the categories and features of multi-sourced rural data such as remote sensing; (2) the computing approaches for rural data and the intelligent interpretation techniques for imagery-figure relationship; (3) the supports from the computed results to rural sustainable developments. Finally, the current challenges as well the further research directions are discussed and envisaged aiming at the Computable Village.